SE1830358A1 - Alcolock device using mapping gaze and motion parameters - Google Patents
Alcolock device using mapping gaze and motion parametersInfo
- Publication number
- SE1830358A1 SE1830358A1 SE1830358A SE1830358A SE1830358A1 SE 1830358 A1 SE1830358 A1 SE 1830358A1 SE 1830358 A SE1830358 A SE 1830358A SE 1830358 A SE1830358 A SE 1830358A SE 1830358 A1 SE1830358 A1 SE 1830358A1
- Authority
- SE
- Sweden
- Prior art keywords
- drunk
- driver
- alcohol
- cognitive
- eye
- Prior art date
Links
- 238000013507 mapping Methods 0.000 title 1
- 238000001514 detection method Methods 0.000 claims abstract description 7
- 230000035945 sensitivity Effects 0.000 claims abstract 2
- 239000003814 drug Substances 0.000 claims description 2
- 229940079593 drug Drugs 0.000 claims description 2
- 230000004424 eye movement Effects 0.000 abstract description 13
- 230000000007 visual effect Effects 0.000 abstract description 12
- 238000012360 testing method Methods 0.000 abstract description 8
- 230000002452 interceptive effect Effects 0.000 abstract description 3
- 206010029864 nystagmus Diseases 0.000 abstract description 2
- 235000019441 ethanol Nutrition 0.000 abstract 13
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 abstract 11
- 230000001149 cognitive effect Effects 0.000 abstract 7
- 230000000694 effects Effects 0.000 abstract 7
- 230000003920 cognitive function Effects 0.000 abstract 5
- 238000013459 approach Methods 0.000 abstract 4
- 239000008280 blood Substances 0.000 abstract 3
- 210000004369 blood Anatomy 0.000 abstract 3
- 210000003169 central nervous system Anatomy 0.000 abstract 3
- 238000000034 method Methods 0.000 abstract 3
- 230000004434 saccadic eye movement Effects 0.000 abstract 3
- 206010039203 Road traffic accident Diseases 0.000 abstract 2
- 208000027418 Wounds and injury Diseases 0.000 abstract 2
- 230000019771 cognition Effects 0.000 abstract 2
- 230000006378 damage Effects 0.000 abstract 2
- 238000005516 engineering process Methods 0.000 abstract 2
- 230000037406 food intake Effects 0.000 abstract 2
- 230000006870 function Effects 0.000 abstract 2
- 208000014674 injury Diseases 0.000 abstract 2
- 238000005259 measurement Methods 0.000 abstract 2
- 230000002265 prevention Effects 0.000 abstract 2
- 230000029058 respiratory gaseous exchange Effects 0.000 abstract 2
- 230000016776 visual perception Effects 0.000 abstract 2
- 241000209202 Bromus secalinus Species 0.000 abstract 1
- 206010019233 Headaches Diseases 0.000 abstract 1
- 230000001154 acute effect Effects 0.000 abstract 1
- 230000004075 alteration Effects 0.000 abstract 1
- 230000006399 behavior Effects 0.000 abstract 1
- 230000003542 behavioural effect Effects 0.000 abstract 1
- 230000004456 color vision Effects 0.000 abstract 1
- 231100000869 headache Toxicity 0.000 abstract 1
- 230000035987 intoxication Effects 0.000 abstract 1
- 231100000566 intoxication Toxicity 0.000 abstract 1
- 230000008447 perception Effects 0.000 abstract 1
- 229940068196 placebo Drugs 0.000 abstract 1
- 239000000902 placebo Substances 0.000 abstract 1
- 230000003449 preventive effect Effects 0.000 abstract 1
- 238000012545 processing Methods 0.000 abstract 1
- 238000011160 research Methods 0.000 abstract 1
- 230000004044 response Effects 0.000 abstract 1
- 230000001052 transient effect Effects 0.000 abstract 1
- 208000006550 Mydriasis Diseases 0.000 description 1
- 201000005111 ocular hyperemia Diseases 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
- B60R25/20—Means to switch the anti-theft system on or off
- B60R25/25—Means to switch the anti-theft system on or off using biometry
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
- A61B3/113—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for determining or recording eye movement
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
- A61B5/163—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state by tracking eye movement, gaze, or pupil change
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
- A61B5/18—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state for vehicle drivers or machine operators
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4845—Toxicology, e.g. by detection of alcohol, drug or toxic products
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60K—ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES; ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS IN VEHICLES; AUXILIARY DRIVES FOR VEHICLES; INSTRUMENTATION OR DASHBOARDS FOR VEHICLES; ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GAS EXHAUST OR FUEL SUPPLY OF PROPULSION UNITS IN VEHICLES
- B60K28/00—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions
- B60K28/02—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions responsive to conditions relating to the driver
- B60K28/06—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions responsive to conditions relating to the driver responsive to incapacity of driver
- B60K28/063—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions responsive to conditions relating to the driver responsive to incapacity of driver preventing starting of vehicles
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
- F02D—CONTROLLING COMBUSTION ENGINES
- F02D41/00—Electrical control of supply of combustible mixture or its constituents
- F02D41/02—Circuit arrangements for generating control signals
- F02D41/021—Introducing corrections for particular conditions exterior to the engine
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2415—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
- G06F18/24155—Bayesian classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
- G06F3/013—Eye tracking input arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
- G06V20/597—Recognising the driver's state or behaviour, e.g. attention or drowsiness
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
- G06V40/19—Sensors therefor
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
- B60W2040/0818—Inactivity or incapacity of driver
- B60W2040/0836—Inactivity or incapacity of driver due to alcohol
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0062—Adapting control system settings
- B60W2050/0063—Manual parameter input, manual setting means, manual initialising or calibrating means
- B60W2050/0064—Manual parameter input, manual setting means, manual initialising or calibrating means using a remote, e.g. cordless, transmitter or receiver unit, e.g. remote keypad or mobile phone
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0062—Adapting control system settings
- B60W2050/0075—Automatic parameter input, automatic initialising or calibrating means
- B60W2050/0083—Setting, resetting, calibration
- B60W2050/0088—Adaptive recalibration
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
- B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
- B60W2420/403—Image sensing, e.g. optical camera
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/043—Identity of occupants
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/221—Physiology, e.g. weight, heartbeat, health or special needs
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/225—Direction of gaze
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/24—Drug level, e.g. alcohol
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2540/00—Input parameters relating to occupants
- B60W2540/26—Incapacity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/178—Human faces, e.g. facial parts, sketches or expressions estimating age from face image; using age information for improving recognition
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Human Computer Interaction (AREA)
- Multimedia (AREA)
- Medical Informatics (AREA)
- Mechanical Engineering (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Animal Behavior & Ethology (AREA)
- Surgery (AREA)
- Molecular Biology (AREA)
- Heart & Thoracic Surgery (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- General Engineering & Computer Science (AREA)
- Pathology (AREA)
- Combustion & Propulsion (AREA)
- Chemical & Material Sciences (AREA)
- Transportation (AREA)
- Psychology (AREA)
- Social Psychology (AREA)
- Developmental Disabilities (AREA)
- Educational Technology (AREA)
- Hospice & Palliative Care (AREA)
- Psychiatry (AREA)
- Ophthalmology & Optometry (AREA)
- Child & Adolescent Psychology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Artificial Intelligence (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Mathematical Physics (AREA)
- Automation & Control Theory (AREA)
- Databases & Information Systems (AREA)
Abstract
Gazelock BACKGROUND From the statistics of Finland, drunk driving is involved in 25 % of fatal traffic accidents. Just in 2011, 74persons died and 735 were injured in traffic accidents that involved drunk driving in Finland[1,4]. It has beenestimated that the cost of a traffic fatality is 1.9 million Euro. A permanent injury costs 1.0 million Euro and atemporary injury on average 241 000 Euro. Furthermore, the statistics shows also that the profile of a drunk driver has not changed for a long period. Aboutone third of drunk drivers are recidivists and the rate has remained at the same level for 30 years. The risk ofbeing caught has not increased for 30 years. A drunk driver can still drive drunken about 220 occasions beforebeing caught[4]. The findings justify an obligatory use of Alcolocks as one preventive measure to counteractrecidivism. Studies from Finland, Sweden, Canada and USA have shown good results of the impact of Alcolockson recidivism [1-4]. One of the serious problems with the existing Alcolocks is that they measure blood alcoholconcentration through some kinds of breathing systems. Technically, such systems can be cheated easily inpractice, for instance, one headache with Alcolock in a real application is to know if a driver cheats it by using amask to filter his/her breathing airs. In this disclosure we invent a new approach to build Alcolocks based on the fact that drinking alcohol willimpair both motor skills and cognitive functioning. The fact can be used to detect if a driver is drunk throughmeasuring his/her motor skills and cognitive fiinctions. More specifically, Alcohol ingestion will cause varying degrees of physiological losses that result in changes inthe cognitive and behavioral functions as well as visual perception [9]. The effects can be felt and measured evenwhen alcohol is consumed in light to moderate levels. Intoxication due to occasional alcohol ingestion will affectthe central nervous system (CNS). These effects of alcohol on the CNS result in alterations in the visual systemthat are related, for instance, to color perception, contrast sensitivity, as well as on eye movements [9]. Eye movement is a good indicator of cognitive functions. One of the main fiinctions of eye movements is toalign information of potential interest and the fovea, thus selecting information from relevant parts of the visualenvironment. Therefore, eye movements are closely related to visual attention. Typical eye movements whilstscanning an image can be classifies as saccades and fixations. Saccades are ballistic movements of the eye itselffrom one point of the visual scene to another, whereas fixations refer to the time between the saccades in whichthe eye presents minimal movements [9]. Since the intake of alcohol will cause transient motor and cognitive changes, when performing a visual searchingtask one needs a large number and duration of fixations, high latency for the initial fixation and a high number ofsaccades, as well as a high total time. As an indicator of cognitive processing eye movement can be used tomeasure the effects of alcohol intake. There are some studies on the effect of alcohol intake on eye movement and visual perception and recognition.In [8] it was concluded that alcohol dose affect human picture perception and decrease the performance of visualexploration. Another study showed that it is possible to see deviations in the gaze patterns of drunk people, evenat a very low level of blood alcohol concentration[9,10]. Measurement of eye movements has been suggested fordetecting a drunk driver. However, it is not an effective and efficient way for drunk detection if patterns of eyemovements and/or eye gaze are measured in some kind of passive way. In this disclosure we invent a robust wayto accurately detect drunk drivers, where to unlock the car the driver has to run an interactive visual test whichhas a high demend of cognitive functions and motor skills. Unlike other approaches, it is not a simplemeasurement of eye movement rather but measurement of deviation in the gaze pattems in a closed hand-eyecoordination process. More specifically, it is not just cognitive functions are measured through eye movementbut the mismatch between cognitive and motor skills that is measured. Our principle is based on the fact that drinking alcohol can impair both motor skills and cognitive functioning,but motor skills can be re-gained at a faster rate than cognitive functions. This could create the illusion ofcomplete sobriety and prompt the undertaking of activities requiring cognitive processes that are still greatlyimpaired. This will result in fatal problems, for example, make incorrect responses very fast, pressing theaccelerator rather than the break in an emergency situation. Therefore, the most effective way is to measure themismatch between motor skills and cognitive functions. The mismatch is a more sensitive effect than use ofcognitive functions alone for detecting drunk drivers. To compute the mismatch we invent a way of measuring motion skills in an interactive visual test process. Letthe driver hold a device or a mobile to run a designed visual test, his/her motion skills can be measured throughphysical motion sensors embedded in the device, or through already existed in modern mobile phones. This isdifferent from some existing approaches of using mobiles to combat drunk driving [6]. In these approaches mobile phones use their accelerometer and orientation sensors to detect patterns associated with driving underthe influence. The sensor data are used to compute driving behaviors but not for measuring personal motor skillsin a visual test as we do. Furthermore, an important requirement for a Working Alcolock is that no helpful to ask others to unlock thealcolock. To reach it one has to make sure that the person unlocking the alcolock should be the same one who isdriving the vehicle. Besides stop drunk driving it is of equal impotance in preventing the misuse of the car bysomeone else for terror attack. Therefore, identifying the personal identity of a driver is extremely important.Besides safety personal identity is also very helpful in making alcolocks more robust. The study in [4] showedthat the time of the survey and the gender of the driver were high risk factors for drunk driving. The risk on a Saturday morning was about eight times higher than during Tuesday afternoon. The risk for a female to drivedrunk was less than one fifth of that for men. Divorced and widowed people had a clearly higher risk than married drivers. In the age group “30-54 years” therisk for drunk driving was higher compared to the age group “below 20 years”. Unemployed drunk drivers hadalso higher blood alcohol concentration. Therefore, the context and personal socioeconomic status will be veryuseful in aiding the detection of drunk driver. Reference: 1. Blincoe,L.J.,Miller,T.R.,Zaloshnja,E.,&Lawrence,B.A.(2015,May).The economic and societal impact ofmotor vehicle crashes, 2010. (Revised)(Report No. DOT HS 812 013). Washington, DC: National HighwayTraffic Safety Administration. 2. NationalHighwayTrafficSafetyAdministration.RetrievedMay1 1201 8from _11gtpjjfwyyyggnlitsaiggyi gjigljy; ' :iså- n,M.,P nttilä,A.,Haukka,J.,Rajalin,S.,Eriksson,C.,Gunnar,T.,... Kuoppasalmi, K. (2013). Profile of adrunk driver and risk factors for drunk driving. Findings in roadside testing in the province of Uusimaa inFinland 1990-2008. Forensic Science International, 231(1-3), 20-27. doi:10.1016/j.forsciint.2013.04.010 5. Møller,M.,Haustein,S.,&Prato,C.G.(2015).Profilingdrunkdrivingrecidivistsin Denmark. Accident Analysis &Prevention, 83, 125-131. doi: 10.1016 /j.aap. 2015 6. Dai,J.,Teng,J.,Bai,X.,Shen,Z.,&Xuan,D.(2010).Mobilephonebaseddrunk driving detection. Proceedings of the4th Intemational ICST Conference on Pervasive Computing Technologies for Healthcare.doi:10.4108/icst.pervasivehealth2010.8901 7. DriverAlcoholDetectionSystemforSafety.httpsz/ß/wwxw'.dadss.tir 8. Moser,A.,Heide,W.,&Kömpf,D.(1998).Theeffectoforalethanolconsumptionon eye movements in healthy volunteers. Joumal of Neurology,245(8), 542-550. doi:10.1007/s004150050240 9. Silva,J.B.,Cristino,E.D.,Almeida,N.L.,Medeiros,P.C.,&Santos,N.A.(2017). Effects of acute alcohol ingestionon eye movements and cognition: A double-blind, placebo-controlled study. Plos One,12(10).doi:10.1371/joumal.pone.0186061 10.Thien, N. H., & Muntsinger, T. Horizontal Gaze Nystagmus Detection in Automotive Vehicles. 11.GHO | By category | Legal BAC limits - Data by country. (n.d.). Retrieved May 10, 2018, from httn :,//'apps,xw'11o. int/ gho/”data/vievsnma in. 54600 3. Bergman, G, Larsson, A, Martinsson, A, Norén, F.(2018) The future of DUI detection technology,- A research study on prevention and methods for detecting drivers under the influence (DUI), KTH Media LabCourse Report.
Description
DETAILED DESCRIPTION One of the most common Ways to determine if someone is under influence of some kind of drug, legal or illegal,is by looking them in the eyes. Dilated pupils, eye redness, nystagmus, problems With fixating gaze, all of thesecould be indicators for a person under the influence. The different impacts on the eyes are how We can takeadvantage of these visual cues to spot a drunk driver before they start driving. A efficent and effective Way to doso is to use eye-tracking to measure if a driver is drunk[3].
Our innovation is to build a device as an Alcolock. To unlock the car the driver needs to orient the device by thehand and/or use the touch screen to finish a visual test running in the screen of the device. The applicationscenario is shown here.
The driver is asked to hold the device to run an interactive visual test. Eye movements are recorded through aneye tracker. The device has a screen on Which the designed visual test is presented for the driver to visualize.Besides the screen the device contains video cameras, physical sensors to record hand gestures, processor,memory and computer operational system. There are four technical modules behind the device: 1) personidentification module; 2) eye gaze tracking module; 3) motor skill computing model; 4) drunk detection module.
Claims (4)
1. There are four technical modules behindthe device: 1) person identification module;
2. ) eye gaze tracking module;
3. ) motorskill computing model;
4. ) drunk detection module. Summary Gazelock is able to stop the society from drug drivers. ln a safe , not cheatable, program in yourmobile or car devic, the car will not start if you are not a safe driver. Studies show the sensitivity andspecificity of the program who will save life's in the future.
Priority Applications (6)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
SE1830358A SE543249C2 (en) | 2018-12-12 | 2018-12-12 | Alcolock device using mapping gaze and motion parameters |
JP2021534255A JP2022512253A (en) | 2018-12-12 | 2019-12-12 | Alcolock devices and systems that use gaze and motor parameter mapping |
PCT/SE2019/051270 WO2020122802A1 (en) | 2018-12-12 | 2019-12-12 | Alcolock device and system using mapping of gaze parameters and motion parameters |
EP19895577.5A EP3894254A4 (en) | 2018-12-12 | 2019-12-12 | Alcolock device and system using mapping of gaze parameters and motion parameters |
CN201980082583.8A CN113329904A (en) | 2018-12-12 | 2019-12-12 | Alcohol lock device and system using mapping of gaze and motion parameters |
US17/312,992 US20220073079A1 (en) | 2018-12-12 | 2019-12-12 | Alcolock device and system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
SE1830358A SE543249C2 (en) | 2018-12-12 | 2018-12-12 | Alcolock device using mapping gaze and motion parameters |
Publications (2)
Publication Number | Publication Date |
---|---|
SE1830358A1 true SE1830358A1 (en) | 2020-06-13 |
SE543249C2 SE543249C2 (en) | 2020-11-03 |
Family
ID=71077408
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
SE1830358A SE543249C2 (en) | 2018-12-12 | 2018-12-12 | Alcolock device using mapping gaze and motion parameters |
Country Status (6)
Country | Link |
---|---|
US (1) | US20220073079A1 (en) |
EP (1) | EP3894254A4 (en) |
JP (1) | JP2022512253A (en) |
CN (1) | CN113329904A (en) |
SE (1) | SE543249C2 (en) |
WO (1) | WO2020122802A1 (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112733633A (en) * | 2020-12-28 | 2021-04-30 | 中国农业大学 | Method for predicting positions of eyes of driver of high-power wheeled tractor |
Families Citing this family (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11565587B2 (en) * | 2019-05-15 | 2023-01-31 | Consumer Safety Technology, Llc | Method and system of deploying ignition interlock device functionality |
US11896376B2 (en) * | 2022-01-27 | 2024-02-13 | Gaize | Automated impairment detection system and method |
EP4345774A1 (en) * | 2022-09-27 | 2024-04-03 | Aptiv Technologies Limited | Diminished driver control detection system, method, and software |
CN115429275A (en) * | 2022-09-30 | 2022-12-06 | 天津大学 | Driving state monitoring method based on eye movement technology |
CN117333927B (en) * | 2023-12-01 | 2024-04-16 | 厦门磁北科技有限公司 | Vehicle-mounted face recognition alcohol detection method and system |
Family Cites Families (33)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
GB0203035D0 (en) * | 2002-02-08 | 2002-03-27 | Univ Bristol | A method of and an apparatus for measuring a person's ability to perform a motor control task |
JP4603264B2 (en) * | 2002-02-19 | 2010-12-22 | ボルボ テクノロジー コーポレイション | System and method for monitoring and managing driver attention load |
DE60330980D1 (en) * | 2002-10-15 | 2010-03-04 | Volvo Technology Corp | METHOD FOR EVALUATING THE HEAD AND EYE ACTION OF A PERSON |
EP1914106A3 (en) * | 2003-06-06 | 2008-09-24 | Volvo Technology Corporation | An attention management system and method |
DE102004005163B3 (en) * | 2004-02-02 | 2005-06-02 | Braun, Uwe Peter, Dipl.-Ing. | Alertness detection device for vehicle driver using intermittent illumination of eye and evaluation of pupil reaction |
WO2005098777A1 (en) * | 2004-03-22 | 2005-10-20 | Volvo Technology Corporation | Method and system for perceptual suitability test of a driver |
EP2303627A4 (en) * | 2008-07-18 | 2015-07-29 | Optalert Pty Ltd | Alertness sensing device |
US8226574B2 (en) * | 2008-07-18 | 2012-07-24 | Honeywell International Inc. | Impaired subject detection system |
US8195406B2 (en) * | 2008-12-03 | 2012-06-05 | International Business Machines Corporation | Estimating consumer status using non-invasive technology |
US20110304465A1 (en) * | 2009-12-30 | 2011-12-15 | Boult Terrance E | System and method for driver reaction impairment vehicle exclusion via systematic measurement for assurance of reaction time |
US8384534B2 (en) * | 2010-01-14 | 2013-02-26 | Toyota Motor Engineering & Manufacturing North America, Inc. | Combining driver and environment sensing for vehicular safety systems |
KR20130123014A (en) * | 2012-05-02 | 2013-11-12 | 강민우 | Drunk driving prevention device |
SE536782C2 (en) * | 2012-08-24 | 2014-08-05 | Automotive Coalition For Traffic Safety Inc | Exhalation test system with high accuracy |
SE536784C2 (en) * | 2012-08-24 | 2014-08-05 | Automotive Coalition For Traffic Safety Inc | Exhalation test system |
US8981942B2 (en) * | 2012-12-17 | 2015-03-17 | State Farm Mutual Automobile Insurance Company | System and method to monitor and reduce vehicle operator impairment |
US8878669B2 (en) * | 2013-01-31 | 2014-11-04 | KHN Solutions, Inc. | Method and system for monitoring intoxication |
US9192334B2 (en) * | 2013-01-31 | 2015-11-24 | KHN Solutions, Inc. | Method and system for monitoring intoxication |
US9002067B2 (en) * | 2013-03-28 | 2015-04-07 | Bytelogics Inc. | Systems and methods for detecting blood alcohol level |
US9210547B2 (en) * | 2013-07-30 | 2015-12-08 | Here Global B.V. | Mobile driving condition detection |
US9298994B2 (en) * | 2014-01-09 | 2016-03-29 | Harman International Industries, Inc. | Detecting visual inattention based on eye convergence |
KR20150086911A (en) * | 2014-01-21 | 2015-07-29 | 자동차부품연구원 | Method for determining drunk driving, drunk driving prevention apparatus using the same and control method thereof |
US9475387B2 (en) * | 2014-03-16 | 2016-10-25 | Roger Li-Chung Wu | Drunk driving prevention system and method with eye symptom detector |
DE102014216208A1 (en) * | 2014-08-14 | 2016-02-18 | Robert Bosch Gmbh | Method and device for determining a reaction time of a vehicle driver |
US10137901B2 (en) * | 2014-11-14 | 2018-11-27 | Daniel Jones | Intoxicated vehicle driver accident reduction system |
US20160148523A1 (en) * | 2014-11-21 | 2016-05-26 | George Winston | Standardized Electronic Performance Impairment Analyzer |
US10690510B2 (en) * | 2015-05-12 | 2020-06-23 | Pedro Renato Gonzalez Mendez | Monitoring system for anticipating dangerous conditions during transportation of a cargo over land |
US9888845B2 (en) * | 2015-06-30 | 2018-02-13 | Antonio Visconti | System and method for optical detection of cognitive impairment |
US9884628B1 (en) * | 2015-09-01 | 2018-02-06 | State Farm Mutual Automobile Insurance Company | Systems and methods for graduated response to impaired driving |
DE102015218306A1 (en) * | 2015-09-23 | 2017-03-23 | Robert Bosch Gmbh | A method and apparatus for determining a drowsiness condition of a driver |
EP3481661A4 (en) * | 2016-07-05 | 2020-03-11 | Nauto, Inc. | System and method for automatic driver identification |
US20180075565A1 (en) * | 2016-09-13 | 2018-03-15 | Ford Global Technologies, Llc | Passenger validation systems and methods |
WO2018142394A2 (en) * | 2017-02-06 | 2018-08-09 | Vayavision Sensing Ltd. | Computer aided driving |
US11221669B2 (en) * | 2017-12-20 | 2022-01-11 | Microsoft Technology Licensing, Llc | Non-verbal engagement of a virtual assistant |
-
2018
- 2018-12-12 SE SE1830358A patent/SE543249C2/en unknown
-
2019
- 2019-12-12 US US17/312,992 patent/US20220073079A1/en not_active Abandoned
- 2019-12-12 CN CN201980082583.8A patent/CN113329904A/en active Pending
- 2019-12-12 JP JP2021534255A patent/JP2022512253A/en active Pending
- 2019-12-12 WO PCT/SE2019/051270 patent/WO2020122802A1/en unknown
- 2019-12-12 EP EP19895577.5A patent/EP3894254A4/en not_active Withdrawn
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112733633A (en) * | 2020-12-28 | 2021-04-30 | 中国农业大学 | Method for predicting positions of eyes of driver of high-power wheeled tractor |
CN112733633B (en) * | 2020-12-28 | 2023-07-28 | 中国农业大学 | Method for predicting eye position of driver of high-power wheeled tractor |
Also Published As
Publication number | Publication date |
---|---|
SE543249C2 (en) | 2020-11-03 |
EP3894254A1 (en) | 2021-10-20 |
US20220073079A1 (en) | 2022-03-10 |
EP3894254A4 (en) | 2022-08-17 |
CN113329904A (en) | 2021-08-31 |
WO2020122802A1 (en) | 2020-06-18 |
JP2022512253A (en) | 2022-02-02 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
SE1830358A1 (en) | Alcolock device using mapping gaze and motion parameters | |
US20220095975A1 (en) | Detection of cognitive state of a driver | |
Tanaka et al. | Features, configuration, and holistic face processing | |
CN108446600A (en) | A kind of vehicle driver's fatigue monitoring early warning system and method | |
US20230043200A1 (en) | Method to determine impaired ability to operate a motor vehicle | |
van Boxtel et al. | Intact recognition, but attenuated adaptation, for biological motion in youth with autism spectrum disorder | |
CN104044460A (en) | Alarm method and device for preventing fatigue driving of motor vehicle | |
US20230009372A1 (en) | Systems and methods for non-intrusive drug impairment detection | |
Koh et al. | Smartphone-based modeling and detection of aggressiveness reactions in senior drivers | |
Suhaiman et al. | Development of an intelligent drowsiness detection system for drivers using image processing technique | |
Jansen et al. | Does agreement mean accuracy? Evaluating glance annotation in naturalistic driving data | |
Wulff et al. | The dynamic and fragile nature of eyewitness memory formation: Considering stress and attention | |
Garg | Detection and security system for drowsy driver by using artificial neural network technique | |
Hardwicke et al. | Concussion knowledge and attitudes amongst competitive cyclists | |
Ashlin Deepa et al. | Drowsiness detection using IoT and facial expression | |
Byrnes et al. | On Using Drivers' Eyes to Predict Accident-Causing Drowsiness Levels | |
Feldhütter et al. | A new approach for a real-time non-invasive fatigue assessment system for automated driving | |
Shaykha et al. | FEER: Non-intrusive facial expression and emotional recognition for driver's vigilance monitoring | |
Mallis et al. | Monitoring alertness by eyelid closure | |
Zangrossi et al. | Autobiographical implicit association test and eye movements: fixations topography enables detection of autobiographical memories | |
Kumar et al. | A literature survey of drunk driving detection approaches | |
Yılmaz et al. | SUST-DDD: A real-drive dataset for driver drowsiness detection | |
US20230293090A1 (en) | Neurophysiological assessment, identification, permission control, monitoring, and notification system for covid-19 | |
SE2030301A1 (en) | Method and system for driving skill feedback | |
Harris | The prevalence of thought disorder in personality-disordered outpatients |